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A Distributed Anytime Algorithm for Dynamic Task Allocation in Multi-Agent Systems

Macarthur, Kathryn, Stranders, Ruben, Ramchurn, Sarvapali and Jennings, Nick (2011) A Distributed Anytime Algorithm for Dynamic Task Allocation in Multi-Agent Systems At Twenty-Fifth Conference on Artificial Intelligence (AAAI), United States. 07 - 11 Aug 2011. , pp. 701-706.

Record type: Conference or Workshop Item (Paper)


We introduce a novel distributed algorithm for multi-agent task allocation problems where the sets of tasks and agents constantly change over time. We build on an existing anytime algorithm (fast-max-sum), and give it significant new capa- bilities: namely, an online pruning procedure that simplifies the problem, and a branch-and-bound technique that reduces the search space. This allows us to scale to problems with hundreds of tasks and agents. We empirically evaluate our algorithm against established benchmarks and find that, even in such large environments, a solution is found up to 31% faster, and with up to 23% more utility, than state-of-the-art approximation algorithms. In addition, our algorithm sends up to 30% fewer messages than current approaches when the set of agents or tasks changes.

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Published date: 7 August 2011
Additional Information: Event Dates: August 7-11, 2011
Venue - Dates: Twenty-Fifth Conference on Artificial Intelligence (AAAI), United States, 2011-08-07 - 2011-08-11
Organisations: Agents, Interactions & Complexity


Local EPrints ID: 272233
ISBN: 978-1-57735-507-6
PURE UUID: 44468b5e-2d3a-49b0-a9d6-d6e72baf398b
ORCID for Sarvapali Ramchurn: ORCID iD

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Date deposited: 28 Apr 2011 11:16
Last modified: 18 Jul 2017 06:33

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Author: Kathryn Macarthur
Author: Ruben Stranders
Author: Sarvapali Ramchurn ORCID iD
Author: Nick Jennings

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